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ORCID25th SDM 2025: Alexandria, VA, USA
- Vagelis Papalexakis, Matteo Riondato, Elena Zheleva, Tim Weninger, Wei Ding:
Proceedings of the 2025 SIAM International Conference on Data Mining, SDM 2025, Alexandria, VA, USA, May 1-3, 2025. SIAM 2025, ISBN 978-1-61197-852-0 - Limai Jiang, Yunpeng Cai:
Automated Learning of Semantic Embedding Representations for Diffusion Models. 1-10 - Arvind Renganathan, Rahul Ghosh, Ankush Khandelwal, Vipin Kumar:
Task Aware Modulation using Representation Learning: An Approach for Few Shot Learning in Environmental Systems. 11-20 - Lei Wang, Yu Shi, Yifei Jin, Jian Li:
OpenFE++: Efficient Automated Feature Generation via Feature Interaction. 21-30 - Yifan Kang, Mengyuan Zhang, Kai Liu:
Acceleration in Low-Rank Tensor Completion. 31-40 - Dzung T. Phan, Matt Menickelly, Tsuyoshi Idé, Jayant Kalagnanam:
Convergence-Guaranteed Elastic Net Graphical Model Estimation with Applications to Anomaly Localization. 41-50 - Emre Sefer:
Anomaly Detection via Graph Contrastive Learning. 51-60 - Long Tan Le, Tung-Anh Nguyen, Han Shu, Suranga Seneviratne, Choong Seon Hong, Nguyen H. Tran:
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection. 61-70 - Shurui Cao, Leman Akoglu:
Trajectory Anomaly Detection with By-Design Complementary Detectors. 71-80 - Asma Ahmed Hashmi, Aigerim Zhumabayeva, Nikita Kotelevskii, Artem Agafonov
, Mohammad Yaqub, Maxim Panov, Martin Takác:
Learning Confident Classifiers in the Presence of Label Noise. 81-113 - Lénaïg Cornanguer, Pierre-François Gimenez:
TADAM: Learning Timed Automata from Noisy Observations. 114-123 - Zhong Chen, Yi He, Di Wu, Wenbin Zhang, Zhiqiang Deng:
ℓ1, ∞ Mixed Norm Promoted Row Sparsity for Fast Online CUR Decomposition Learning in Varying Feature Spaces. 124-133 - Yunrui Zhang, Gustavo Batista, Salil S. Kanhere:
Label Shift Estimation With Incremental Prior Update. 134-142 - Ryosuke Takayama, Masanao Natsumeda:
Constraint-Focused Training for Multistate Survival Analysis with Neural Networks. 143-151 - Benjamin A. Miller, Zohair Shafi, Wheeler Ruml, Yevgeniy Vorobeychik, Tina Eliassi-Rad, Scott Alfeld:
Defense Against Shortest Path Attacks. 152-160 - Akash Choudhuri, Yongjian Zhong, Mehrdad Moharrami, Christine Klymko, Mark Heimann, Jayaraman J. Thiagarajan, Bijaya Adhikari:
Conformal Edge-Weight Prediction in Latent Space. 161-170 - Felix I. Stamm, Mehdi Naima, Michael T. Schaub:
Efficient Sampling of Temporal Networks with Preserved Causality Structure. 171-180 - Wenhan Zhang, Zijian Song, Yihuan Wu, Lifang Deng, Jiandong Zhang, Kaigui Bian, Bin Cui:
StarRec: A Hypergraph-based Framework with Star-Expansion for Multi-Behavior Recommendation. 181-191 - Igor L. R. Azevedo, Toyotaro Suzumura, Yuichiro Yasui:
A Look Into News Avoidance Through AWRS: An Avoidance-Aware Recommender System. 192-202 - Renqi Jia, Xiaokun Zhang, Bowei He, Qiannan Zhu, Weitao Xu, Jiehao Chen, Chen Ma:
Beyond Models! Explainable Data Valuation and Metric Adaption for Recommendation. 203-212 - Haipeng Li, Jiangxia Cao, Yiwen Gao, Yunhuai Liu, Shuchao Pang:
CDSRNP: Cross-Domain Sequential Recommendation via Neural Process. 213-222 - Filipa Valdeira, Cláudia Soares:
Ranking with Confidence for Large Scale Comparison Data. 223-232 - Elena Battaglia, Ruggero G. Pensa:
Differentially Private Associative Co-clustering. 233-241 - Minhui Xie, Hao Peng, Pu Li, Guangjie Zeng, Shuhai Wang, Jia Wu, Peng Li, Philip S. Yu:
Hierarchical Superpixel Segmentation via Structural Information Theory. 242-251 - Shangdi Yu, Laxman Dhulipala, Jakub Lacki, Nikos Parotsidis:
DynHAC: Fully Dynamic Approximate Hierarchical Agglomerative Clustering. 252-260 - Walid Durani, Dominik Mautz, Claudia Plant, Christian Böhm:
DMDHC: Discovery of Multi-Density Hierarchical Cluster Structures. 261-269 - Yorgos Tsitsikas, Evangelos E. Papalexakis:
Multi-View Spectral Clustering for Graphs with Multiple View Structures. 270-278 - Zelong Hao, Haitao Zhang, Yang Che, Wang Liu:
Inter-Well Active Magnetic Ranging with Temporal and Interaction Network. 279-287 - Yang Hu, Feng Wu, Xin Li, Yu Yang:
Unanticipated Replenishment: Online Policy for Dynamic Service Composition in Manufacturing Cloud. 288-296 - Yiming Sun, Runlong Yu, Runxue Bao, Yiqun Xie, Ye Ye, Xiaowei Jia:
Domain-Adaptive Continual Meta-Learning for Modeling Dynamical Systems: An Application in Environmental Ecosystems. 297-306 - Yu Qin, Chengshang Zhang, Wei Xu:
Bridging Numbers and Narratives: Enhancing Financial Market Risk Predictions through Numerical Information from Financial Documents. 307-316 - Ruirui Liu, Huichou Huang, Johannes Ruf, Haoxian Liu, Qingyao Wu:
Context-Aware Frequency-Embedding Networks for Spatio-Temporal Portfolio Selection. 317-326 - Zahra Khanjani, Vandana P. Janeja, Christine Mallinson, Sanjay Purushotham:
Blue Sky: Expert-in-the-Loop Representation Learning Framework for Audio Anti-Spoofing: Multimodal, Multilingual, Multi-speaker, Multi-attack (4M) Scenarios. 327-330 - Fatimah Alotaibi, Adithya Kulkarni, Dawei Zhou:
Heterogeneous Multi-Agent Framework for Dynamic Generalized Category Discovery. 331-334 - Adithya Kulkarni, Mohna Chakraborty:
Blue Sky: Reducing Performance Gap between Commercial and Open-Source LLMs. 335-338 - David C. Anastasiu:
Explainable AI for Real-Time Video Anomaly Anticipation. 339-342 - Li Zhang:
Evaluating Time Series Models with Knowledge Discovery. 343-346 - Fanglan Chen, Dongjie Wang, Jianfeng He, Shuo Lei, Chang-Tien Lu:
Optimizing Transit Network Expansion with Gated Attentive Graph Reinforcement Learning. 347-355 - Chaofan Li, Till Riedel, Michael Beigl:
Feature Deviation Embedding Improves Graph Structure Learning for Spatial Interpolation. 356-365 - Shuhan Song, Ping Li, Ming Dun, Yuan Zhang, Huawei Cao, Xiaochun Ye:
Equipping Graph Autoencoders: Revisiting Masking Strategies from a Robustness Perspective. 366-375 - Zohair Shafi, Germans Savcisens, Tina Eliassi-Rad:
REGE: A Method for Incorporating Uncertainty in Graph Embeddings. 376-385 - Tiejin Chen, Longchao Da, Huixue Zhou, Pingzhi Li, Kaixiong Zhou, Tianlong Chen, Hua Wei:
Protecting Privacy against Membership Inference Attack with LLM Fine-tuning through Flatness. 386-397 - Yaohua Wang, Bolin Ding, Rong Zhu, Haibin Wang, Zhijian Ma, Jingren Zhou:
Language Models are Explorers for Join Discovery on Data Lakes. 398-408 - Huaiyuan Yao, Longchao Da, Vishnu Nandam, Justin Turnau, Zhiwei Liu, Linsey Pang, Hua Wei:
CoMAL: Collaborative Multi-Agent Large Language Models for Mixed-Autonomy Traffic. 409-418 - Guoquan Lu, Lin Peng, Li Li:
CoT-Decoding: Complex Reasoning via Chain-of-Thought Decoding. 419-430 - Sikun Guo, Guangzhi Xiong, Aidong Zhang:
Optimizing External and Internal Knowledge of Foundation Models for Scientific Discovery. 431-434 - Adam S. Charles:
Data mining the functional architecture of the brain's circuitry. 435-438 - Runlong Yu, Yiqun Xie, Xiaowei Jia:
What We Talk About When We Talk About AI for Science. 439-442 - Yana Bromberg, Amarda Shehu:
Better AI For Understanding Life on Earth: Predict First, Design Later. 443-446 - Han Meng, Ruoqiao Chen, Bin Chen, Jiayu Zhou:
AnchorDrug: A system for drug-induced gene expression prediction in new contexts through active learning. 447-456 - Jiaming Cui, Bijaya Adhikari, Arash Haddadan, A. S. M. Ahsan-Ul-Haque, Jilles Vreeken, Anil Vullikanti, B. Aditya Prakash:
Accurately Estimating Unreported Infections using Information Theory. 457-466 - Yiqing Zhang, Xiaozhong Liu, Fabricio Murai:
MEXA-CTP: Mode Experts Cross-Attention for Clinical Trial Outcome Prediction. 467-475 - Akash Choudhuri, Hieu Vu, Kishlay Jha, Bijaya Adhikari:
Domain Knowledge Augmented Contrastive Learning on Dynamic Hypergraphs for Improved Health Risk Prediction. 476-486 - Majid Farhadloo, Arun Sharma, Alexey A. Leontovich, Svetomir N. Markovic, Shashi Shekhar:
Spatially-Delineated Domain-Adapted AI Classification: An Application for Oncology Data. 487-496 - Witold Wydmanski, Ulvi Movsum-zada, Jacek Tabor, Marek Smieja:
VisTabNet: Adapting Vision Transformers for Tabular Data. 497-506 - Dingli Su, Hao Peng, Guangjie Zeng, Pu Li, Angsheng Li, Yicheng Pan:
Emergence of Cooperation in Multi-Agent Reinforcement Learning via Coalition Labeling and Structural Entropy. 507-515 - Marcin Osial, Daniel Marczak, Bartosz Zielmski:
Parameter-Efficient Interventions for Enhanced Model Merging. 516-526 - Muhammad Rajabinasab, Anton Danholt Lautrup, Arthur Zimek:
Metrics for Inter-Dataset Similarity with Example Applications in Synthetic Data and Feature Selection Evaluation. 527-537 - Rongchao Xu, Zhiqing Hong, Guang Wang:
AutoSTDiff: Autoregressive Spatio-Temporal Denoising Diffusion Model for Asynchronous Trajectory Generation. 538-547 - MohammadReza EskandariNasab, Shah Muhammad Hamdi, Soukaina Filali Boubrahimi:
AVATAR: Adversarial Autoencoders with Autoregressive Refinement for Time Series Generation. 548-557 - Wang-Tao Zhou, Zhao Kang, Sicong Liu, Lizong Zhang, Ling Tian:
Fine-grained Spatio-temporal Event Prediction with Self-adaptive Anchor Graph. 558-567 - Boje Deforce, Meng-Chieh Lee, Bart Baesens, Estefanía Serral Asensio, Jaemin Yoo, Leman Akoglu:
End-To-End Self-Tuning Self-Supervised Time Series Anomaly Detection. 568-577 - Guangji Bai, Ziyang Yu, Zheng Chai, Yue Cheng, Liang Zhao:
Staleness-Alleviated Distributed GNN Training via Online Dynamic-Embedding Prediction. 578-587 - Ruomeng Ding, Xujiang Zhao, Chen Zhao, Minglai Shao, Zhengzhang Chen, Haifeng Chen:
Evidence-Based Out-of-Distribution Detection on Multi-Label Graphs. 588-597 - Emir Ceyani, Han Xie, Baturalp Buyukates, Carl Yang, Salman Avestimehr:
FedGrAINS: Personalized SubGraph Federated Learning with AdaptIve Neighbor Sampling. 598-607 - Donald Loveland, Danai Koutra:
Unveiling the Impact of Local Homophily on GNN Fairness: In-Depth Analysis and New Benchmarks. 608-617 - Xiaodong Yang, Xiaoting Li, Huiyuan Chen, Yiwei Cai:
GAIM: Attacking Graph Neural Networks via Adversarial Influence Maximization. 618-626 - Hongsheng Liu, Dzung T. PhaC:
Hybrid Bayesian Optimization with DIRECT. 627-636 - Renato Assunção, Flávio Figueiredo, Francisco N. Tinoco Júnior, Léo M. de Sá-Freire, Fábio Silva:
An Interpretable Measure for Quantifying Predictive Dependence between Continuous Random Variables. 637-646 - Nikolaj Tatti:
Approximating splits for decision trees quickly in sparse data streams. 647-655 - Yuta Nambu, Masahiro Kohjima, Tomoharu Iwata, Ryuji Yamamoto:
Meta-learning of Class Knowledge in Zero-shot Learning. 656-665
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